From de6266010d21fdbf30c3221e808301072725d14d Mon Sep 17 00:00:00 2001
From: Pierre Chapuis <git@catwell.info>
Date: Fri, 19 Jan 2024 14:33:56 +0100
Subject: [PATCH] fix typo (sinuosoidal -> sinusoidal)

---
 src/refiners/foundationals/latent_diffusion/range_adapter.py  | 4 ++--
 .../latent_diffusion/stable_diffusion_xl/unet.py              | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/refiners/foundationals/latent_diffusion/range_adapter.py b/src/refiners/foundationals/latent_diffusion/range_adapter.py
index ce24232..fc1da00 100644
--- a/src/refiners/foundationals/latent_diffusion/range_adapter.py
+++ b/src/refiners/foundationals/latent_diffusion/range_adapter.py
@@ -32,14 +32,14 @@ class RangeEncoder(fl.Chain):
         self.sinusoidal_embedding_dim = sinusoidal_embedding_dim
         self.embedding_dim = embedding_dim
         super().__init__(
-            fl.Lambda(self.compute_sinuosoidal_embedding),
+            fl.Lambda(self.compute_sinusoidal_embedding),
             fl.Converter(set_device=False, set_dtype=True),
             fl.Linear(in_features=sinusoidal_embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
             fl.SiLU(),
             fl.Linear(in_features=embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
         )
 
-    def compute_sinuosoidal_embedding(self, x: Int[Tensor, "*batch 1"]) -> Float[Tensor, "*batch 1 embedding_dim"]:
+    def compute_sinusoidal_embedding(self, x: Int[Tensor, "*batch 1"]) -> Float[Tensor, "*batch 1 embedding_dim"]:
         return compute_sinusoidal_embedding(x, embedding_dim=self.sinusoidal_embedding_dim)
 
 
diff --git a/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py b/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
index efa4bc9..afab21a 100644
--- a/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
+++ b/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
@@ -28,7 +28,7 @@ class TextTimeEmbedding(fl.Chain):
                 fl.Chain(
                     fl.UseContext(context="diffusion", key="time_ids"),
                     fl.Unsqueeze(dim=-1),
-                    fl.Lambda(func=self.compute_sinuosoidal_embedding),
+                    fl.Lambda(func=self.compute_sinusoidal_embedding),
                     fl.Reshape(-1),
                 ),
                 dim=1,
@@ -49,7 +49,7 @@ class TextTimeEmbedding(fl.Chain):
             ),
         )
 
-    def compute_sinuosoidal_embedding(self, x: Tensor) -> Tensor:
+    def compute_sinusoidal_embedding(self, x: Tensor) -> Tensor:
         return compute_sinusoidal_embedding(x=x, embedding_dim=self.time_ids_embedding_dim)